Cognitive radio networks

Prepared by: Ameer Sameer Hamood
University of Babylon
Information technology - information networks
Cognitive Radio Networks

Overview
Brief history & Introduction
Characteristics of Cognitive Radio
Cognitive Radio Networks Architecture
Security Issues
Attacks on Cognitive Networks
Cognitive Radio Network Applications
Popular Cognition Techniques
future research direction
Conclusions

Brief history
The term cognitive radio was coined by Mitola in an article he wrote
with Maguire in 1999
and refers to a smart radio that has the ability to sense the external
environment, learn from the history and make intelligent decisions to
adjust its transmission parameters according
to the current state of the environment.

Introduction
The radio spectrum is divided into licensed and unlicensed
frequencies.
The licensed spectrum is for the exclusive use of designated users. For
instance, it includes the UHF/VHF TV frequency bands.
The unlicensed spectrum can be freely accessed by any user, following
certain rules (e.g., not exceeding a defined limit for transmission
power). It includes, for instance, the ISM (Industrial, Scientific and
Medical) and U-NII (Unlicensed National Information Infrastructure)
frequency bands. ISM is shared by technologies such as IEEE 802.11
for wireless local area networks (WLANs), Bluetooth .

The key enabling technology of dynamic spectrum access is
cognitive radio (CR) has emerged as one of the keys that
can help addressing the inefficient usage of the radio
spectrum. It exploits unused licensed radio frequencies,
often designated as spectrum holes see (Figure 1). or white
spaces. CR aims to enable secondary users to autonomously
access spectrum holes in the entire spectrum to increase
performance, as long as they do not harmfully interfere
with primary users. Basically, at a given time and location.
Introduction

(Figure 1) spectrum holes.
Introduction

In order to share the spectrum with licensed users without disturbing
them, and meet the diverse quality of service requirement of
applications, each CR user in a CRN must:
* Determine the portion of spectrum that is available, which is known
as Spectrum sensing.
* Select the best available channel, which is called Spectrum decision.
* Coordinate access to this channel with other users, which is known
as Spectrum sharing.
* Vacate the channel when a licensed user is detected, which is
referred as Spectrum mobility.
See figure (1) Cognitive Cycle .
Introduction

figure (1) Cognitive Cycle
Introduction

cognitive Radio have main characteristics :
1- Cognitive capability
2- Reconfigurable Capability
3- self-organized capability
We can summarize 1- Cognitive capability as follows:
Spectrum sensing
Location identification
Network/system discovery
Service discovery

2- Reconfigurable Capability :
Frequency agility
Dynamic frequency selection
Adaptive modulation/coding (AMC)
Transmit power control (TPC)
Dynamic system/network access

3- self-organized capability
With more intelligence to communication terminal devices, CRs
should be able to self-organize their communication based on sensing
and reconfigurable functions . see figure (3.S) below

The basic components of CRNs are the mobile station (MS),
base station/access point (BSs/APs) and backbone/core
networks. These three basic components compose three kinds
of network architectures in CRNs:
1- Network architectures
2- Links in CRN
3- IP Mobility Management in CRN

Here only explain network architectures in CRNs:
1- Network architectures
A- Infrastructure-Based
B- Ad-hoc Architecture
C- Mesh Architecture

1- Infrastructure-Based
In the Infrastructure architecture (Figure 1.1), a MS can only access
a BS/AP in the one-hop manner. MSs under the transmission range of
the same BS/AP shall communicate with each other through the
BS/AP. Communications between different cells are routed through
backbone/core networks. The BS/ AP may be able to run one or
multiple communication standards/protocols to fulfil different
demands from MSs. A cognitive radio terminal can also access various
kinds of communication systems through their BS/AP.

Figure 1.1 Infrastructure architecture of a CRN

2- Ad-hoc Architecture
There is no infrastructure support in ad-hoc architecture (Figure 2.1).
The network is set up on the fly. If a MS recognizes that there are
some other MSs nearby and they are connectable through certain
communication standards/protocols, they can set up a link and thus
form an ad-hoc network. Note that these links between nodes may be
set up by different communication technologies. In addition, two
cognitive radio terminals can either communicate with each other by
using existing communication protocols (e.g., WiFi, Bluetooth) or
dynamically using spectrum holes .

Figure 2.1 Ad-hoc architecture of a CRN

3- Mesh Architecture
This architecture is a combination of the infrastructure and ad-hoc
architectures plus enabling the wireless connections between the BSs/APs
(Figure 3.1).
This network architecture is similar to the Hybrid Wireless Mesh Networks.
the BSs/APs work as wireless routers and form wireless backbones.
MSs can either access the BSs/APs directly or use other MSs as multi-hop
relay nodes.
Some BSs/APs may connect to the wired backbone/core networks and
function as gateways.
. If the BSs/APs have cognitive radio capabilities, they may use spectrum
holes to communicate with each other

Figure 3.1 Mesh architecture of a CRN

2- Links in CRN

3- IP Mobility Management in CRN

Security Issues
The question is how to protect the licensed spectrum and
users and also how to avoid unlicensed users from causing
interference with existing licensed users or use of special
reserved frequencies like, e.g., for emergency services.
Other possible security risks are involuntary downloading
of malicious software, licensed user emulation

We define an attack on cognitive networks as any activity that results
in :
(a) unacceptable interference to the licensed primary users
Or
(b) missed opportunities for secondary users.
An attack is considered strong if it involves a minimal number of
adversaries performing minimal operations but causing maximum
damage/loss to the primary and or secondary users in the network.
See figure (A.1) explain Layer Attacks :

figure (A.1)

Cognitive Radio Networking and Opportunistic Spectrum Access can
be used in different applications:
1- Cognitive Mesh Networks
2- Public Safety Networks
3- Disaster Relief and Emergency Networks
4- Battlefield Military Networks
5- Leased Networks

1- Cognitive Mesh Networks
Multi-hop wireless mesh networks have recently gained significant
popularity as a cost-effective solution for last-mile Internet access.
Traditional wireless mesh network are challenged by the scarcity of
the wireless bandwidth needed to meet the high-speed requirements of
existing wireless applications.
by allowing the mesh nodes to dynamically explore any available
spectral opportunities. Such cognitive mesh networks are meant be
used to provide broadband access to rural, tribal, and other under-
resourced regions.
See figure (1.C) explain Cognitive Mesh Networks

figure (1.C) Cognitive Mesh Networks

2- Public Safety Networks
Public safety networks are used for communications among police
officers and fire and paramedic personnel. Such networks are also
challenged by the limited amount of allocated spectrum. Even with
the recent extensions of the allocated public safety spectrum bands,
the public safety personnel do not have the technology to dynamically
operate across the different spectrum segments. Recall that public
safety licensees have a wide variety of bands available (VHF-Low,
VHFHi,220MHz, UHF below 800, UHF-800, etc.). The cognitive radio
technology can offer public safety networks more bandwidth through
Opportunistic Spectrum Access. Furthermore, a public safety CRN
can provide a substantial communication improvement by allowing
the interpretability across different public safety services while
smartly adapting to the high peak-to-average nature of the traffic
carried out by such networks. See figure (2.P)

figure (2.P) Public Safety Networks

3- Disaster Relief and Emergency Networks
Natural disasters such as hurricanes, earthquakes, wild fires, or other
unpredictable phenomena usually cause the communications infrastructure to
collapse. For example, some base stations of cellular networks can fall, the
connectivity between sensor nodes and the sink node in static wireless sensor
networks can be lost, existing Wireless Local Area Networks (WLANs) can be
damaged, etc. This results in a set of partially or fully damaged coexistent
networks that were previously deployed and then became disconnected.
Meanwhile, there is an urgent need for a means of communications to help
the rescue teams to facilitate organized help, rehabilitation efforts, and to
locate the disaster survivors. CRNs can be used for such emergency networks.
provide a significant amount of bandwidth that can handle the expected huge
amount of voice, video, and other critical and time-sensitive traffic
See figure (3.D)

figure (3.D) Disaster Relief and Emergency Networks

4- Battlefield Military Networks
Unfortunately, the recent advances in wireless technologies made the
job of communication jamming and/or hacking much easier.
Consequently, achieving reliable and secure communications in
modern battlefields has become a more challenging task. Recall that a
battlefield communication network provides the only means of
communications between soldiers, armed vehicles, and other units in
the battlefield amongst themselves as well as with the headquarters.
This implies that such networks do not only require significant
amount of bandwidth, but also mandate secure and reliable
communications to carry vital information. The cognitive radio is the
key enabling technology for realizing such densely deployed networks
which use distributed Opportunistic Spectrum Access strategies to
fulfill the bandwidth and reliability needs . see figure (4.B)

figure (4.B) Battlefield Military Networks

5- Leased Networks
All of the aforementioned CRN applications have the secondary users
exploiting the resources of the primary networks without being
beneficial to the primary networks in any way. However, a primary
network can benefit from leasing a fraction of its licensed spectrum to
secondary operators adopting cognitive radio technology to
opportunistically access the spectrum. The entrance of the secondary
operator to the market of the incumbent primary network can
increase the revenue of the primary licensed operator. See figure(5.L)

figure(5.L) Leased Networks

Popular Cognition Techniques
A list of popular cognition techniques that can be used in CF for the
control of CRNs :
Bayesian signal processing
Dynamic programming
Learning machines with feedback
Game theory
Dynamic frequency management
Software defined radio
Cross-layer protocol design

future research direction
A. Seamless spectrum handovers
B. Proactive spectrum selection and interference avoidance
C. Interdependency between the propagation characteristics of radio
signals and the frequency band in usage
D. Alternatives to the common channel
E. Energy efficiency
F. Validation of CR protocols

Conclusions
1- The radio spectrum is statically allocated and divided between
licensed and unlicensed frequencies.
2- Cognitive Radio is a recent network paradigm that enables a more
flexible and efficient usage of the radio spectrum.
3- The status of a wireless channel can change due to several reasons in
CR, such as node mobility, operating frequency, neighbor interference,
transmission power and primary user appearance.
4-The architecture of CR networks can either be centralized or
distributed.
5- The capabilities of cognitive radios as nodes of CRN can be classified
according to their functionalities based on the definition of cognitive
radio.

Reference
1- Cognitive Radio Networks Book by:
Professor Kwang-Cheng Chen
National Taiwan University, Taiwan
Professor Ramjee Prasad
Aalborg University, Denmark
2- COGNITIVE NETWORKS Towards Self-Aware Networks
Edited by
Qusay H. Mahmoud
University of Guelph, Canada
3- Cognitive Radio Networks
Edited by
Yang Xiao • Fei Hu

4- Cognitive Radio Networks Implementation and Application issues
in India By Lokesh Chouhan , Under the supervision of Prof. Aditya
Trivedi , ABV – Indian Institute of information , Technology &
Management, Gwalior
5- cognitive Radio Network
from Theory to Practice , Springer
Khattab ,A ;Perkins ,D;Bayoumi,M 2013,ISBN:978-1-4614-4032-1
6- Cognitive Radio Networks
Adrian Popescu Dept. of Communications and Computer Systems
School of Computing Blekinge Institute of Technology 371 79 Karlskrona,
Sweden
Reference

7- Cognitive Radio: Technology Survey and Future Research
Directions By : José Marinho , CISUC, University of Coimbra
ISEC, Polytechnic Institute of Coimbra , Coimbra, Portugal
Edmundo Monteiro , CISUC, University of Coimbra ,Coimbra,
Portugal
Reference

Cognitive radio networks

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